|
|
Absolute deviation, 绝对离差' { W& u! C. s% P7 }
Absolute number, 绝对数
; X0 | e* P0 q$ b$ ^% m3 ^Absolute residuals, 绝对残差
: q5 {) u2 x/ y0 i+ N! uAcceleration array, 加速度立体阵* c8 U: Q* }7 f/ |2 E& J7 i# |
Acceleration in an arbitrary direction, 任意方向上的加速度; }* {8 T* h: A( V; @% X
Acceleration normal, 法向加速度
2 f8 p- {" ?! [; _6 q+ o! ]Acceleration space dimension, 加速度空间的维数
) B* d- M: Y- jAcceleration tangential, 切向加速度9 W' s' P( l' k/ z/ b7 r( L% ]
Acceleration vector, 加速度向量
& z; B4 e5 ~$ W9 |Acceptable hypothesis, 可接受假设
4 l4 a* ?' K! X' p* VAccumulation, 累积
- |7 R0 I& P ]2 K3 D; A L7 GAccuracy, 准确度# k+ j: M# u! k3 N% o' p
Actual frequency, 实际频数; p' X/ `2 V! ^/ V
Adaptive estimator, 自适应估计量 u, r& l, h' `2 `/ }) |
Addition, 相加
; Y: |2 x1 X5 U5 W5 BAddition theorem, 加法定理4 z8 |/ R H% B$ o9 ~, g; @
Additivity, 可加性
+ c2 G) |, C9 C/ Z' MAdjusted rate, 调整率' x L9 U( j- B5 {/ G2 ~, @
Adjusted value, 校正值4 a: t5 _8 ^: h2 g( ?6 g/ l( p4 q
Admissible error, 容许误差5 z- v# e6 M! }5 `; O/ Z% n
Aggregation, 聚集性6 _2 f& N6 F+ W/ \- u# a
Alternative hypothesis, 备择假设
. ` F% T+ t& s+ }Among groups, 组间6 j/ J( F% g, o& q0 `
Amounts, 总量 {6 W1 s& a4 M2 z9 S' h% c
Analysis of correlation, 相关分析# r: M$ t. L3 f" y
Analysis of covariance, 协方差分析) Y5 w [/ @8 O7 M$ m: R
Analysis of regression, 回归分析
6 R* T8 ?1 k" g4 cAnalysis of time series, 时间序列分析% Q* R+ Z7 d- h2 h, L; Y
Analysis of variance, 方差分析
0 P! }; R8 r1 }! s U, {: T+ WAngular transformation, 角转换4 u h w; D; R
ANOVA (analysis of variance), 方差分析
6 I: r/ G U& X: JANOVA Models, 方差分析模型0 f* Z" y3 Y" H- r0 t
Arcing, 弧/弧旋: @" h8 N6 V& {: q* x9 Y8 b
Arcsine transformation, 反正弦变换
1 @, y* y1 I: y" ?Area under the curve, 曲线面积
F2 t @/ s4 G5 j9 aAREG , 评估从一个时间点到下一个时间点回归相关时的误差
. K, C5 O7 M4 j& t lARIMA, 季节和非季节性单变量模型的极大似然估计 4 N5 @& G0 A5 s4 F3 o% ]* }
Arithmetic grid paper, 算术格纸
% a$ r. g6 V- vArithmetic mean, 算术平均数
1 ]0 R8 A m6 {' ~2 U3 ?3 @- VArrhenius relation, 艾恩尼斯关系
' q9 t9 v. I, w, u; L7 hAssessing fit, 拟合的评估
h5 R! B0 ^3 u7 h- eAssociative laws, 结合律! T% u% o* z8 y: R: I
Asymmetric distribution, 非对称分布
6 ]0 W/ W6 [4 i5 eAsymptotic bias, 渐近偏倚
0 o+ A9 a% ` W, {! }: k: @Asymptotic efficiency, 渐近效率
( x9 L1 _, m8 d, e3 r2 |" Y. ZAsymptotic variance, 渐近方差 s# r% Q8 x$ s% I. k; l5 k
Attributable risk, 归因危险度0 \, Y h8 h2 j8 A/ g% j4 Z
Attribute data, 属性资料, Z4 ^: g% f. |+ A) D& U4 z) l
Attribution, 属性7 T; [4 q4 u& o' J1 A
Autocorrelation, 自相关. [& j/ c M! D, k% J3 T
Autocorrelation of residuals, 残差的自相关& `$ ]9 |6 F1 U" i; a6 ~
Average, 平均数7 S. I; R6 H! `) N3 {
Average confidence interval length, 平均置信区间长度& G6 ~$ c* i+ ~. x
Average growth rate, 平均增长率 F1 N1 o' o2 [) H% B* k
Bar chart, 条形图
' e" B0 g" f# x! v7 B3 QBar graph, 条形图
0 |' M) g" y" M8 V6 |; t2 q7 E+ @Base period, 基期
! f/ I* E& a4 rBayes' theorem , Bayes定理
1 x: D/ \7 k9 P- ]$ l" I9 nBell-shaped curve, 钟形曲线( e" x/ ^% S' X( l1 I
Bernoulli distribution, 伯努力分布
7 l0 o$ E! D! \Best-trim estimator, 最好切尾估计量
' d4 D. ^$ r7 G: bBias, 偏性
, W/ I4 s2 x, l( ~Binary logistic regression, 二元逻辑斯蒂回归
4 X' g6 H) m1 j8 S' pBinomial distribution, 二项分布+ v7 S7 H+ v, h: H0 s5 j
Bisquare, 双平方3 G3 @' B4 W8 z3 n+ ]3 d
Bivariate Correlate, 二变量相关
' c5 M2 r: _; m$ J u0 }Bivariate normal distribution, 双变量正态分布" ~) w4 R+ U! B5 d3 L6 I9 b3 }
Bivariate normal population, 双变量正态总体! n0 E1 f( c- w9 [( e2 U
Biweight interval, 双权区间+ ^) _( f# s& N5 \( l9 K7 @6 _
Biweight M-estimator, 双权M估计量
+ D) N, S/ T Z) OBlock, 区组/配伍组
J6 }. m/ ~( i* {6 l8 H xBMDP(Biomedical computer programs), BMDP统计软件包
3 ]% ~: Q+ h" E( d( a' jBoxplots, 箱线图/箱尾图
2 Y: L, N: m% N3 `, D! pBreakdown bound, 崩溃界/崩溃点$ V, T% e. Q# l, b' N5 r
Canonical correlation, 典型相关
1 D) {& S% |5 X p, ?# r# W; BCaption, 纵标目1 {* x; B' I* ^4 w* V
Case-control study, 病例对照研究
7 Q2 |9 ~8 }& [; `8 oCategorical variable, 分类变量
( e" I, W, c1 |1 N$ k: S4 |, V+ iCatenary, 悬链线
$ ~6 L; L" R* `+ b6 cCauchy distribution, 柯西分布 O P: y2 p4 u. \4 G* T
Cause-and-effect relationship, 因果关系" E& M/ h+ j' i' H" j* F2 l4 p% i
Cell, 单元
& m/ [/ E$ }6 o& }; |5 w1 ~Censoring, 终检* V( @# v- q$ v m5 F
Center of symmetry, 对称中心5 J2 V. A; K) ~' _& Z& q g
Centering and scaling, 中心化和定标; b; ?# I8 \! _# X# I9 |' m
Central tendency, 集中趋势
2 Y5 k/ W; k' G# L/ v1 WCentral value, 中心值7 x) ?& ~7 l k# p! k
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
& b; @1 O H# oChance, 机遇; R1 V7 i4 s' P
Chance error, 随机误差
" |" u: f6 `1 JChance variable, 随机变量6 z; n5 H$ K" ?: n9 G' Z M5 m- F
Characteristic equation, 特征方程
& ~$ N& S, `, Q# I: N: kCharacteristic root, 特征根
2 O# [6 ^1 v: }0 j7 h }( eCharacteristic vector, 特征向量
6 X: A7 E9 Y6 j8 EChebshev criterion of fit, 拟合的切比雪夫准则
. P2 T( G# l# [- XChernoff faces, 切尔诺夫脸谱图
' r) i% {0 e, \5 `! yChi-square test, 卡方检验/χ2检验) u: g. y2 d+ G2 X4 S
Choleskey decomposition, 乔洛斯基分解: u% N. I; K' A4 o1 ]* o( X
Circle chart, 圆图 5 N3 }: y& @* Z! x$ q% H# h
Class interval, 组距
3 p- ^6 @ h ?9 PClass mid-value, 组中值" x) J6 R: {$ x% f# [" C
Class upper limit, 组上限( e$ ?0 S* c9 x, z- n
Classified variable, 分类变量2 A9 K& B# l& O
Cluster analysis, 聚类分析' r; X( ~/ X$ `. P- {9 O6 f
Cluster sampling, 整群抽样
/ L: E- E. F/ b4 ?1 vCode, 代码
, d C4 e& i9 u5 hCoded data, 编码数据
( K+ o& I( M1 N3 B/ y) ]8 GCoding, 编码: D. m( S4 ?) w
Coefficient of contingency, 列联系数; b' K! b a! K, }
Coefficient of determination, 决定系数
: t, A8 y& [2 O7 |( MCoefficient of multiple correlation, 多重相关系数+ D0 m ~# m& v
Coefficient of partial correlation, 偏相关系数
! Z- b3 J' g) ICoefficient of production-moment correlation, 积差相关系数5 i# Q- ]+ [% {5 O. ?
Coefficient of rank correlation, 等级相关系数$ V0 K7 @/ }% C6 ]3 T8 V8 F7 Q
Coefficient of regression, 回归系数
8 Z: E; ^3 j9 N% iCoefficient of skewness, 偏度系数% W) S0 a% p5 s
Coefficient of variation, 变异系数
2 N. G+ U2 a3 ?4 L# v2 K. }; ACohort study, 队列研究; X$ D# n6 J8 ^$ `7 M& i0 a
Column, 列
% E8 n$ M. H. M, e9 \2 S- z5 C0 @8 AColumn effect, 列效应
, v+ K( z: x' U* CColumn factor, 列因素) ?: z6 H0 `$ N& M6 \% ^5 ?! r) {
Combination pool, 合并
/ a6 d+ J# O1 H' e! c: J- \' \8 CCombinative table, 组合表
% F* I# E" p1 `1 F6 T8 fCommon factor, 共性因子9 [8 {7 L' V4 B
Common regression coefficient, 公共回归系数
" X1 D+ s9 k: S% ]& fCommon value, 共同值
% l4 s: I4 u) i# UCommon variance, 公共方差3 X; s% T+ @3 V& F
Common variation, 公共变异
; K+ { `7 R+ s" g9 I1 y% xCommunality variance, 共性方差# _! T5 V7 ?! p2 u) c9 V
Comparability, 可比性
8 i' [/ F! I5 @5 v( C1 lComparison of bathes, 批比较: Z M; U0 t2 s! G3 C0 V4 k
Comparison value, 比较值1 F, m% E5 [& Y& X$ c
Compartment model, 分部模型
/ w5 Y5 }4 S5 l; O; rCompassion, 伸缩
* X* O0 {; R, S6 q6 W8 AComplement of an event, 补事件) ?! J5 u6 ?% O5 V1 i0 S7 d: v G
Complete association, 完全正相关
, X s7 X( g& r) vComplete dissociation, 完全不相关4 S; J" Q- e+ Q1 v& u
Complete statistics, 完备统计量
6 p' A: r; x, M8 ~5 cCompletely randomized design, 完全随机化设计
e6 ~% Z( i/ Z/ G* h* b" V% cComposite event, 联合事件" b, R5 o0 ~ P" e7 l. a
Composite events, 复合事件
* m: E5 m+ e9 lConcavity, 凹性& C3 i. S" p1 o8 e
Conditional expectation, 条件期望: k+ a4 x2 C( W: r% J
Conditional likelihood, 条件似然4 F# Z- c+ q7 c1 w7 }3 s
Conditional probability, 条件概率! `% B$ L" y! R3 y7 g$ F& r
Conditionally linear, 依条件线性: K' N/ H, s+ n+ c* Y7 W
Confidence interval, 置信区间
`$ h: t- |+ m( }9 Z" ` _ gConfidence limit, 置信限
; Z% A. Z* g6 X3 I: z, yConfidence lower limit, 置信下限
* ~! k( J) ^; vConfidence upper limit, 置信上限1 X* {1 W6 g; ?" Q
Confirmatory Factor Analysis , 验证性因子分析
8 A) |9 Q( P: PConfirmatory research, 证实性实验研究, A+ o6 B9 Z/ P, m8 O' n0 Q+ w
Confounding factor, 混杂因素
\/ j. [8 E- M* _( PConjoint, 联合分析1 E, g6 {6 _6 c
Consistency, 相合性% x, B' s6 p, ?, F# w4 c
Consistency check, 一致性检验 Q) m2 h' X; N: b
Consistent asymptotically normal estimate, 相合渐近正态估计
& A* r$ G5 z! W; b2 o7 ~2 NConsistent estimate, 相合估计0 a/ ]* S) ?) B8 m. m- c
Constrained nonlinear regression, 受约束非线性回归$ r) J$ ^0 Z; p# _1 r5 \$ U# A
Constraint, 约束" ?' B- X4 z2 U4 E% i$ j
Contaminated distribution, 污染分布
4 J* _' H- n' yContaminated Gausssian, 污染高斯分布- Y6 i) H+ T9 D' L' f' M
Contaminated normal distribution, 污染正态分布
& }; d, @8 T3 w% i, |% n1 F. aContamination, 污染& u# D, r E: t8 Q% B, I( o: h
Contamination model, 污染模型
R6 S% Q- N2 M8 RContingency table, 列联表/ A& }7 s; z% @& V4 R2 S
Contour, 边界线* D/ L4 p9 ?' \4 N# l
Contribution rate, 贡献率* o% C- [% D$ x% e! t" t3 |
Control, 对照
! ~5 ^. U- ?' Q DControlled experiments, 对照实验
: ]' \- P8 f7 F/ hConventional depth, 常规深度% {* [: {3 ]/ @) _
Convolution, 卷积
( G0 U( l/ p# w) NCorrected factor, 校正因子
E8 b, r+ D' zCorrected mean, 校正均值3 I! T, x9 T: g# q+ J# j% H7 s! N
Correction coefficient, 校正系数' g( C3 s2 M8 Q* T
Correctness, 正确性' z: f' J" P, m4 C. |
Correlation coefficient, 相关系数* A% x: W4 I W d9 l ]
Correlation index, 相关指数
5 g+ i, k- k6 Z& l4 e8 ICorrespondence, 对应
4 b4 m4 O) X: x& D) X0 W8 z# wCounting, 计数. |6 k+ O% Q+ H' b7 z# Q
Counts, 计数/频数
% V! Q) m. m ZCovariance, 协方差( _: v; A( q7 Q0 l" e6 P
Covariant, 共变 9 R" t& Z8 A& l! m9 q' [
Cox Regression, Cox回归. a: S: g4 m7 F" B
Criteria for fitting, 拟合准则& T7 \. h+ ]+ z, d2 Z
Criteria of least squares, 最小二乘准则( l2 U% l: `9 m* R
Critical ratio, 临界比
6 R5 }5 R4 W6 l g8 L2 F/ V2 I! vCritical region, 拒绝域
8 E+ @. e+ ]" w3 ~ m: ~' b, V GCritical value, 临界值
0 g- N! T- T; c9 y7 S# L, OCross-over design, 交叉设计6 E7 e3 b2 L' g5 R
Cross-section analysis, 横断面分析' Y1 Q" }$ z7 L8 X
Cross-section survey, 横断面调查" w8 c# g2 [6 \& ^/ E" _5 R& ~& G
Crosstabs , 交叉表 / i! ?: u' A* r
Cross-tabulation table, 复合表( s0 m8 H" F( z
Cube root, 立方根5 _) t" N$ C- I
Cumulative distribution function, 分布函数
$ a4 \0 e) M8 O. [- fCumulative probability, 累计概率
4 T) {" G0 Z; A' [- `9 i5 H3 p& F& ?9 m8 OCurvature, 曲率/弯曲/ ]) I1 v$ ~1 Q U& H
Curvature, 曲率
& u7 p/ b( B% ~- n' M! d8 X! L3 eCurve fit , 曲线拟和
' m1 g) ?% X. V/ Y8 lCurve fitting, 曲线拟合
, \ V& K- \" h/ ?& Y& rCurvilinear regression, 曲线回归3 H+ q$ _) g. y, z+ z( s4 K
Curvilinear relation, 曲线关系7 [$ d) U& h' h
Cut-and-try method, 尝试法
# B7 v, Q% e& G' ]4 QCycle, 周期; L8 m# V, Z2 ~
Cyclist, 周期性" ]: I+ s5 n! V* K F) ?: p/ Q% K
D test, D检验
, C. [8 T* i3 u: u3 `* [Data acquisition, 资料收集! }: F- o; d' B8 v
Data bank, 数据库
- g3 K3 ]) |0 ]. K( R2 D* H+ m) |& }Data capacity, 数据容量
2 q$ Q/ {6 s3 z) N: TData deficiencies, 数据缺乏, I6 p) \( G' B+ j
Data handling, 数据处理9 H2 R/ r4 c# b$ V
Data manipulation, 数据处理
; I. T2 a2 L9 {* p' W$ R! e" \' K9 NData processing, 数据处理
$ f6 O/ h ~7 q- B# rData reduction, 数据缩减
0 B3 n! n( ^; q- s- s3 {* M1 w- |Data set, 数据集" ~7 h( Z' U: W" _+ z$ C
Data sources, 数据来源
: y8 n) Y8 _! q7 v# v2 `Data transformation, 数据变换! U& b V, G( t9 y b% i
Data validity, 数据有效性8 Y! x5 F2 @2 S& h. T) l
Data-in, 数据输入
! W6 p% N% K4 ^/ U& UData-out, 数据输出
1 F( }& A- s5 z8 C; V g1 zDead time, 停滞期
) z( i# Y8 i3 l# a6 X9 @1 |Degree of freedom, 自由度; I7 D/ E/ X) }! \' r" U
Degree of precision, 精密度' x5 V* q* h6 b
Degree of reliability, 可靠性程度
& i H8 ]- e& Z! d6 z( |Degression, 递减
6 b/ M' U3 J0 z' ?Density function, 密度函数
8 a M9 Q4 [* TDensity of data points, 数据点的密度 x$ v4 D1 a) v% m/ d5 h9 D4 G
Dependent variable, 应变量/依变量/因变量
* W8 ~+ `0 U4 DDependent variable, 因变量
3 J- j [# s! R7 eDepth, 深度- L! i8 g7 F6 U! h* s+ ]6 b$ T
Derivative matrix, 导数矩阵* y6 H3 Y; E; A& O6 [8 S" e5 |" j
Derivative-free methods, 无导数方法
9 }0 b, A, l8 o7 BDesign, 设计
9 Q8 ]! o: V. H8 D2 n. N8 W P UDeterminacy, 确定性' m/ [" v3 h3 @7 C! ~
Determinant, 行列式8 ~7 u% k' u6 f2 @
Determinant, 决定因素! h7 l& C& P0 ~) C& d
Deviation, 离差* A$ d0 T" g) O [$ g8 X( [3 H
Deviation from average, 离均差% [- k& c8 A6 l& E) T0 L
Diagnostic plot, 诊断图0 o# I( O* x. Q% t. R6 ^- L' v
Dichotomous variable, 二分变量
$ X: m+ K- K) ^3 WDifferential equation, 微分方程
8 }4 \; p1 W/ O1 D* C' n% M" ]& i, nDirect standardization, 直接标准化法' s; T$ o, s- Y7 D: }( X6 G
Discrete variable, 离散型变量0 w0 G! L5 u/ T; r3 _8 ?( I
DISCRIMINANT, 判断 % y4 E! }0 U5 ?9 e
Discriminant analysis, 判别分析
' Z9 T0 ?+ m8 ^Discriminant coefficient, 判别系数8 Y5 c1 q0 P. E D0 k6 O1 W
Discriminant function, 判别值
% v5 g( {# I' t+ U0 EDispersion, 散布/分散度
4 P) j( j7 C5 U/ o# E& D6 w* YDisproportional, 不成比例的/ j3 u9 l; M! s3 ?3 n
Disproportionate sub-class numbers, 不成比例次级组含量, W. X6 b; C* c! T1 e' m
Distribution free, 分布无关性/免分布
) S B# S- k9 ?Distribution shape, 分布形状) M* f& F7 K C, Q) s6 c/ c4 ^
Distribution-free method, 任意分布法7 h7 E5 y5 B. Q& x( T0 W
Distributive laws, 分配律
& }5 O6 W. y, f9 ]2 S3 eDisturbance, 随机扰动项- ?8 [* w3 g! N+ |* \ y
Dose response curve, 剂量反应曲线6 j& R9 N" P# k0 R
Double blind method, 双盲法/ c; Z2 B' M8 r& ~( q$ d1 t
Double blind trial, 双盲试验
) X [7 U& S$ p9 B& g: S9 [. qDouble exponential distribution, 双指数分布
6 O/ h5 y/ g7 O4 ]( @Double logarithmic, 双对数2 R5 M, c9 E0 J" C9 o7 O
Downward rank, 降秩
) }: E: m# @+ c1 X1 D' aDual-space plot, 对偶空间图" V( r% o0 E. {" g5 Q; {
DUD, 无导数方法2 {! s; e% F6 T) D1 W
Duncan's new multiple range method, 新复极差法/Duncan新法& _$ I/ j: j* x8 |" P
Effect, 实验效应3 P1 O0 ~" f' B, p7 h1 K9 u2 ?
Eigenvalue, 特征值% V( C, D3 A6 h5 k
Eigenvector, 特征向量 K8 N5 p- @9 y0 V: ]. ~8 j
Ellipse, 椭圆; y7 R; a; {4 _! Z! b/ b3 D
Empirical distribution, 经验分布- Y- E8 L6 ^( _& O6 Q3 b
Empirical probability, 经验概率单位
2 i% u/ H$ z% _) ?Enumeration data, 计数资料
0 g! T2 G: k& J" `Equal sun-class number, 相等次级组含量- X9 j4 }0 Q' Z* a& u1 L& V) A
Equally likely, 等可能
' Z% c; Y) y# A1 L5 }Equivariance, 同变性' F, n# V" t5 h/ d6 H
Error, 误差/错误6 o/ y$ O; H% I2 i3 y: F% W
Error of estimate, 估计误差6 R8 k- D7 V' Y2 A; J9 Z. t
Error type I, 第一类错误
+ V5 A" \3 p$ |Error type II, 第二类错误( r+ h; _, v; F* M G' J. D: r) d, o
Estimand, 被估量
) v& N' i w$ A. _! t7 VEstimated error mean squares, 估计误差均方
) s4 ^5 ^1 _/ Q) ]1 U$ e. KEstimated error sum of squares, 估计误差平方和) @4 T7 J6 X& \4 }9 |! V) G$ d
Euclidean distance, 欧式距离
* _2 H, u \% h! S7 L+ O9 KEvent, 事件
/ N' ?9 z f8 V) {2 r# j4 LEvent, 事件
& A. @' b, p! A& t4 t- cExceptional data point, 异常数据点: @& M1 q8 g4 w# V7 R) J: i0 v
Expectation plane, 期望平面
0 s; B. W( F) M9 ]Expectation surface, 期望曲面
) x" x- y. @( ~ `Expected values, 期望值
- {! {$ j7 v7 R0 dExperiment, 实验
# }4 _4 |% T" G1 d' k0 }( J$ v3 JExperimental sampling, 试验抽样7 S! @ _% ~8 m; }) R/ G. N6 j
Experimental unit, 试验单位$ P9 o+ e. C7 V; T! y5 \7 R' F
Explanatory variable, 说明变量
- G& o0 V r. ^0 `Exploratory data analysis, 探索性数据分析 T+ t C! Z1 z1 _
Explore Summarize, 探索-摘要
2 |9 q8 n, e/ J" v' R# i" D3 S$ QExponential curve, 指数曲线
2 i3 q( U$ N. `# a% C* y+ m0 {1 S8 mExponential growth, 指数式增长0 Q6 e# B/ S* ]/ U8 W" o! |* a
EXSMOOTH, 指数平滑方法
4 k9 o; ^, j. ] z6 W' e" dExtended fit, 扩充拟合
1 S' r+ A: m9 |% dExtra parameter, 附加参数
! a( n$ n. @5 Z+ M! q4 yExtrapolation, 外推法
% S8 m3 t# H$ K- K) CExtreme observation, 末端观测值
/ d; R- U2 o1 {0 z. ^/ KExtremes, 极端值/极值1 Y' R3 N$ h, @; {
F distribution, F分布
4 q/ u) [" D h. l* p; B' D$ i0 @8 RF test, F检验
2 N8 f8 b/ ]" n# r8 ^5 R4 ^Factor, 因素/因子0 s! _# k, A2 B7 O
Factor analysis, 因子分析% k& _, M/ C' i* ]" z7 t: i
Factor Analysis, 因子分析
6 s3 w* X9 A+ e$ E$ PFactor score, 因子得分 ' y# j; U5 [6 F
Factorial, 阶乘
2 f7 B1 D f1 C2 m6 z. n& JFactorial design, 析因试验设计, A+ x, R6 W7 l$ ~2 O- @# G: n
False negative, 假阴性* r0 p+ O$ G ^4 L
False negative error, 假阴性错误
, n9 ~; q2 G m4 pFamily of distributions, 分布族
* W! b% z% |9 d2 R& k3 K7 W6 H# lFamily of estimators, 估计量族
8 Q2 s7 O6 J: j* |0 L5 N+ _5 lFanning, 扇面5 y5 H, i' `' R& m( T
Fatality rate, 病死率" q% Q# n+ v4 ~; i6 E8 N! k0 O
Field investigation, 现场调查
J/ |( ^! p9 FField survey, 现场调查
7 J( A8 W A5 k- x) KFinite population, 有限总体3 k# c8 w+ E5 l& z
Finite-sample, 有限样本9 _: ^" }8 U: h' }: I
First derivative, 一阶导数
" s$ J# M( i" n1 p' rFirst principal component, 第一主成分( W" h l. T; n2 X9 Z) R7 i4 t; h
First quartile, 第一四分位数
( R" a# S) u2 Z7 qFisher information, 费雪信息量2 _) f/ d# ?3 \* T$ M! L8 h( {3 c
Fitted value, 拟合值
7 R' N+ T+ c5 y* s% }& HFitting a curve, 曲线拟合4 c% _0 P. k; D' o K3 Z0 p
Fixed base, 定基9 ?+ @. h: C- Y) A; O7 c
Fluctuation, 随机起伏
5 C0 k; A' D* A& ~Forecast, 预测" G8 V: {" F$ }' \/ l% M0 ^
Four fold table, 四格表6 e9 F. K" x! j* c- H$ Y! d- t
Fourth, 四分点
! K' X' I( q3 L" vFraction blow, 左侧比率
2 K! K. H. c$ i" B( UFractional error, 相对误差) @+ A* [! O- u5 g6 u
Frequency, 频率5 O% G& a8 _/ s' d. ]
Frequency polygon, 频数多边图
+ f4 M0 Q- L$ K# RFrontier point, 界限点( o1 [9 l7 @ m
Function relationship, 泛函关系
+ i. C7 M4 r3 Q& n/ FGamma distribution, 伽玛分布4 }" y8 @% d# V/ c4 C
Gauss increment, 高斯增量1 u* A f( w& V
Gaussian distribution, 高斯分布/正态分布9 k. w3 m- _$ D, a2 |
Gauss-Newton increment, 高斯-牛顿增量
+ a. l# T2 M! C% U1 k5 A2 O2 qGeneral census, 全面普查
% J$ n! P, Y. J) ^+ w5 \GENLOG (Generalized liner models), 广义线性模型 0 u' u/ _) W8 c: `
Geometric mean, 几何平均数9 B5 e( B8 j/ q
Gini's mean difference, 基尼均差
' s1 F+ x* K- TGLM (General liner models), 一般线性模型 5 Y* q7 b [4 n9 C
Goodness of fit, 拟和优度/配合度, \& I, y# P0 [" ?5 s5 u
Gradient of determinant, 行列式的梯度, r0 S+ I: I% W( W3 N
Graeco-Latin square, 希腊拉丁方3 @) P! l k$ m- K. F
Grand mean, 总均值
; I! @2 R. O- n1 O* k- I( T( O, FGross errors, 重大错误- H( J) G, l+ [
Gross-error sensitivity, 大错敏感度
, O! {. |5 p7 S, l# u5 s1 [Group averages, 分组平均
4 F5 p$ e% N$ ^5 {: _; A! M8 |Grouped data, 分组资料# ^) i& x' G! \8 {& _! c+ G2 k
Guessed mean, 假定平均数 G4 i+ z' K9 J
Half-life, 半衰期
6 s6 N" @* H0 a/ e# BHampel M-estimators, 汉佩尔M估计量
2 G& V0 ]& E; |( k$ J/ B2 k YHappenstance, 偶然事件
. Y- Z0 J ?1 Q: X7 { c6 B/ eHarmonic mean, 调和均数# T9 G/ ?+ J% [; P& o
Hazard function, 风险均数' I0 o, L& {4 R, H2 a2 e* v1 r
Hazard rate, 风险率
/ f9 ~6 V) I) C9 P. w0 V; hHeading, 标目
9 \% E/ m$ E6 x) }Heavy-tailed distribution, 重尾分布/ d! Y& i. f" W7 F& |
Hessian array, 海森立体阵
, z7 K6 r4 _3 `# l8 w2 ~. ]4 M2 UHeterogeneity, 不同质
5 d1 [3 W, V4 s* G( l; Q. THeterogeneity of variance, 方差不齐
3 X6 D# S6 R, ]Hierarchical classification, 组内分组
( g6 i4 b7 H$ h6 @Hierarchical clustering method, 系统聚类法" I! K- V. r J! H+ t
High-leverage point, 高杠杆率点: o3 g5 A4 A+ W5 ^1 C6 M7 d- q
HILOGLINEAR, 多维列联表的层次对数线性模型9 H- `( |: S+ z1 _* H" R
Hinge, 折叶点0 y! L3 j2 Q* _4 ?+ }* }6 P# C: T( Q
Histogram, 直方图% f4 s: M- d: S% ^8 h
Historical cohort study, 历史性队列研究
, j7 @/ Y+ | A. `9 O$ J' q& O: qHoles, 空洞7 g1 [, M* T+ @6 T& r3 z3 b
HOMALS, 多重响应分析" Y& W1 n5 h, X& q9 n% b3 a3 X
Homogeneity of variance, 方差齐性6 K. z: K y' v4 d
Homogeneity test, 齐性检验* f0 U9 N7 v8 Q/ T# ~0 A
Huber M-estimators, 休伯M估计量
2 y" C" I- j' [0 c) ^Hyperbola, 双曲线
% r- ^$ z8 x, Y; _# S# y: \Hypothesis testing, 假设检验& ^. L, ~: N) i3 _
Hypothetical universe, 假设总体! Q3 g6 d8 E& _$ V$ E3 h
Impossible event, 不可能事件
, U8 c- {5 {8 b- }1 ^) qIndependence, 独立性4 p8 {1 i* L* M" T& o7 b' f
Independent variable, 自变量/ S. D6 ^5 [& z/ K# P! ]- ?
Index, 指标/指数$ B K) [: N. T- ?$ m) t9 h$ W
Indirect standardization, 间接标准化法
4 {+ `. T- _- w' \: h( LIndividual, 个体6 S3 T; A5 S0 u' T# I1 j1 Q% I% m% s
Inference band, 推断带) E3 A2 C' p5 N' J0 g% n Z
Infinite population, 无限总体/ H E O6 M5 a9 w
Infinitely great, 无穷大4 N6 V# b" ^0 ~
Infinitely small, 无穷小! \/ d- ?, n1 _& t5 {
Influence curve, 影响曲线5 B9 z2 o- s3 c1 N: `+ a1 c
Information capacity, 信息容量2 S- i0 @( H7 D! X1 r* u9 |
Initial condition, 初始条件
d6 m$ N6 X# ?& jInitial estimate, 初始估计值
9 G. u7 A# X1 |" }- bInitial level, 最初水平
; y! O' R u$ \5 EInteraction, 交互作用
/ r9 V; n$ N. J: I( i% i! o* AInteraction terms, 交互作用项
' H% \& s! X+ MIntercept, 截距" R. Y# s `: x' F) q. B& q
Interpolation, 内插法
1 t& `$ o8 Q( m W0 H. `, t9 |" DInterquartile range, 四分位距( j) E1 ^ U$ N ?9 V2 _
Interval estimation, 区间估计
6 L; z( z7 Q4 F$ v2 jIntervals of equal probability, 等概率区间
, c2 V G+ Q; }. Y* J0 y' }Intrinsic curvature, 固有曲率
! u& ? N% V5 S+ a* k. @Invariance, 不变性
" R* F* c' `7 i/ l, V5 x& SInverse matrix, 逆矩阵
. S8 s# B1 n! f! NInverse probability, 逆概率
4 {' r7 t" j @ _8 g% Q9 ~& ^7 hInverse sine transformation, 反正弦变换
$ j% }. D i" R% f7 Y6 CIteration, 迭代
1 P7 s% g( u8 C# k, aJacobian determinant, 雅可比行列式1 U3 Y) ~& n" Y% R
Joint distribution function, 分布函数
. V/ A- g2 i, d& I7 a+ jJoint probability, 联合概率+ _3 T$ u' Y. q- ^- u' | [2 z( S8 _
Joint probability distribution, 联合概率分布
: n0 H* `1 P- ~' O) [: ?K means method, 逐步聚类法
$ N! {' k' k( DKaplan-Meier, 评估事件的时间长度 ! M. a. z& G0 m' @$ L
Kaplan-Merier chart, Kaplan-Merier图4 T2 Q+ ?3 m+ j0 A/ R& K
Kendall's rank correlation, Kendall等级相关
7 P2 c6 i d1 N# v0 PKinetic, 动力学0 Y1 }! E) o8 f, g+ _2 Y
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
: }& v- W5 @- B9 @Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验* a- [6 k9 h: Y1 z' ]/ G
Kurtosis, 峰度+ N* H. r6 L; h1 m6 H
Lack of fit, 失拟
2 H' B2 R, a, ~7 |/ mLadder of powers, 幂阶梯
8 Q4 [8 ?/ S& TLag, 滞后* H, N+ E+ t1 k1 u) C; L* U
Large sample, 大样本/ i. _7 j& s9 x2 }/ z8 l5 ]9 _
Large sample test, 大样本检验
8 M: G/ h2 c9 d" V, FLatin square, 拉丁方
$ [6 v2 S5 e4 d7 U8 y$ o& MLatin square design, 拉丁方设计
" s+ r) |9 {- E8 t5 v9 w9 S5 @Leakage, 泄漏
1 ~6 n a4 Z* R$ J- T& vLeast favorable configuration, 最不利构形
g2 W& P0 Z7 K! r0 g4 cLeast favorable distribution, 最不利分布
1 ~! l$ Y9 v* y8 Q$ z' D+ xLeast significant difference, 最小显著差法! m) s0 j- O) c8 v/ N9 l- [
Least square method, 最小二乘法6 x# ~. [, x6 j0 P7 J1 x O
Least-absolute-residuals estimates, 最小绝对残差估计
. i& Y0 y! R7 v I7 q' D4 rLeast-absolute-residuals fit, 最小绝对残差拟合
; d! K( G+ E) l' dLeast-absolute-residuals line, 最小绝对残差线' ~4 U$ [' O3 U
Legend, 图例/ P, u6 ]. s- X/ r" |6 J# G! f! P$ f
L-estimator, L估计量; r$ G) K2 H( e2 o
L-estimator of location, 位置L估计量
7 G1 B7 Y- c o- G& z% Z' KL-estimator of scale, 尺度L估计量
3 q7 W8 F( P* ?8 q& @6 \6 lLevel, 水平+ l7 ]4 c W! S* q( w4 z; O3 b
Life expectance, 预期期望寿命
: t# N, m0 X! K: jLife table, 寿命表- b+ ~: E# m6 T8 r% U! G
Life table method, 生命表法
! c/ b7 T* }0 A; q5 {: T2 \Light-tailed distribution, 轻尾分布% ]$ D' c, L. m+ h; d
Likelihood function, 似然函数: q# O! h: O A" M
Likelihood ratio, 似然比
4 [' g- F ?& q! Aline graph, 线图% y6 \& O- X4 Y5 F3 I& P# }' j
Linear correlation, 直线相关% u: W6 h8 [3 N1 M7 c7 W2 j
Linear equation, 线性方程
8 r1 G+ G- v4 t, @Linear programming, 线性规划. h+ K) f' k3 W
Linear regression, 直线回归
* J) q6 J& ^+ R( u( xLinear Regression, 线性回归
: g( J- I3 e! S1 l2 y* g% C# sLinear trend, 线性趋势
! O4 j% j7 U6 e) ~( ~9 a# T" \& tLoading, 载荷 9 h. M/ T6 S2 o9 b( F
Location and scale equivariance, 位置尺度同变性7 x b3 T5 `( z' i4 m" T3 x4 L
Location equivariance, 位置同变性
% @2 q" k! V- g% Y# BLocation invariance, 位置不变性
1 J @* l( F! PLocation scale family, 位置尺度族 c- Y+ t3 X( r+ r* b$ n" ?
Log rank test, 时序检验
& R, d* r- B& S- u# ^! Y& [Logarithmic curve, 对数曲线1 N6 p+ s. z. W& o* v. ?+ j& Q
Logarithmic normal distribution, 对数正态分布
$ Y0 W" ^, _: O P2 ALogarithmic scale, 对数尺度
' n" |7 u9 G4 A; ^* R, ^+ l7 MLogarithmic transformation, 对数变换. @( A# d) o1 J+ |/ o4 f- c* Z& u
Logic check, 逻辑检查
. v+ u9 f7 J. u4 W3 i9 Q5 zLogistic distribution, 逻辑斯特分布
5 m: x& Y1 Q; a! m% T& NLogit transformation, Logit转换4 E# b/ s5 I7 `, N' |, b
LOGLINEAR, 多维列联表通用模型
% Z3 X- p% D) C# W3 p/ D2 _) hLognormal distribution, 对数正态分布+ i/ \+ Q2 i: C% ]2 U2 a4 q
Lost function, 损失函数7 D# }, p! M0 k- V* s+ S
Low correlation, 低度相关
/ r& D( v4 e8 f6 uLower limit, 下限 G$ j4 P# H/ A, o. j! O# H
Lowest-attained variance, 最小可达方差
/ A- W3 L; E& Z4 hLSD, 最小显著差法的简称. M; U. j* \# P) v( @
Lurking variable, 潜在变量! p5 {9 e3 g+ I
Main effect, 主效应5 j6 v" N2 X: w4 y
Major heading, 主辞标目
+ L0 @0 s9 H% p5 _' _Marginal density function, 边缘密度函数( ?3 @# ]$ z7 h5 l: ?, s( z
Marginal probability, 边缘概率
& Y% t; L/ ~/ A1 t" ~3 E3 `: z& WMarginal probability distribution, 边缘概率分布
& U% j( w. k2 h% U9 GMatched data, 配对资料4 f) G+ p+ O) D: F: _* S
Matched distribution, 匹配过分布
+ |: u! b# K! T+ H, O* J5 ]6 yMatching of distribution, 分布的匹配
0 c0 N6 L4 D3 Q: x( D( V! e+ EMatching of transformation, 变换的匹配. H) X/ C% g7 i9 m- a6 j+ x
Mathematical expectation, 数学期望% f! ?( H& N5 S1 P
Mathematical model, 数学模型
8 s1 o9 P, n% |Maximum L-estimator, 极大极小L 估计量1 q) A1 l' S7 @4 l$ k2 w y& S" T
Maximum likelihood method, 最大似然法
# u* C( I" e9 x8 iMean, 均数
# D" ?( h4 N" ~0 [- s5 `9 iMean squares between groups, 组间均方
6 @' z9 D9 \/ ^% ?Mean squares within group, 组内均方
% d: G9 O# t) @* f: y2 ~$ mMeans (Compare means), 均值-均值比较* h9 V3 ?( {. p7 v
Median, 中位数
. \1 p6 e7 K% u$ E3 b4 {" h% a, DMedian effective dose, 半数效量
! I: G- g/ `- ]Median lethal dose, 半数致死量* c/ t, q( ^' e# D; ?! T. m5 W# i% B
Median polish, 中位数平滑
2 R; S' O$ P: _$ x7 I( T9 ^; h/ MMedian test, 中位数检验
k$ M# u8 f [! N EMinimal sufficient statistic, 最小充分统计量# @: t; U( a6 L% ?
Minimum distance estimation, 最小距离估计
5 Z$ L- R; P9 fMinimum effective dose, 最小有效量
( a" ?, v5 [! U! qMinimum lethal dose, 最小致死量- F3 ]. b% G! Q \- z* |( H
Minimum variance estimator, 最小方差估计量, z$ w. B4 y l9 H
MINITAB, 统计软件包
4 S1 q" j& s2 Q2 c' h$ c) g; wMinor heading, 宾词标目; K8 C3 x8 e' N3 Z% ^7 d
Missing data, 缺失值
' @4 \$ O4 T2 J0 z8 pModel specification, 模型的确定- M; H/ J# Q$ V8 d ~
Modeling Statistics , 模型统计( v0 `( H: y! }2 u, u1 T
Models for outliers, 离群值模型 v+ \) x" H S7 @0 Q5 D
Modifying the model, 模型的修正+ t0 f. B4 b; V, K6 q1 |
Modulus of continuity, 连续性模5 p t. J; W/ M3 Y
Morbidity, 发病率
6 ~0 s6 J9 G# A/ V f3 E' b! MMost favorable configuration, 最有利构形3 J, A+ J! e$ ^! j. V
Multidimensional Scaling (ASCAL), 多维尺度/多维标度3 I5 S$ c0 p( }
Multinomial Logistic Regression , 多项逻辑斯蒂回归' G \0 u( e+ ~) M
Multiple comparison, 多重比较
, M2 Q6 D$ O8 ]2 F2 UMultiple correlation , 复相关3 H7 \, X1 u4 \' E
Multiple covariance, 多元协方差
$ Q3 i. Z, [9 eMultiple linear regression, 多元线性回归
# n& j% p! M: K& t( z- {. W# uMultiple response , 多重选项% y+ @* v/ X! j8 e" }' ^" o F9 S. R
Multiple solutions, 多解
1 A6 G9 ^4 |$ C9 AMultiplication theorem, 乘法定理
- L: u6 H- I# R( Z w6 E1 ^# S% H, _Multiresponse, 多元响应
. i: p/ E( j$ J# g jMulti-stage sampling, 多阶段抽样
! H, W# ^) e1 p% W+ |) ^' t' b' J$ UMultivariate T distribution, 多元T分布
: Q0 m! Y' z4 bMutual exclusive, 互不相容! h" U! w7 o* V! l# M2 F( @
Mutual independence, 互相独立3 s4 J7 p* W* L$ I0 |$ T$ T
Natural boundary, 自然边界
; ~% U0 i' h0 j4 X) p/ MNatural dead, 自然死亡
9 q3 i( Y- `$ U+ W8 cNatural zero, 自然零/ {4 z* z$ u$ n7 [3 l, M
Negative correlation, 负相关
7 y9 b7 \! P; f: sNegative linear correlation, 负线性相关4 f- x( d0 ?! |* ~2 Q9 C( m6 x
Negatively skewed, 负偏0 |( G. L" [( U; _) N% q3 r2 ^
Newman-Keuls method, q检验
5 ^# T7 r% a0 }' b: |/ QNK method, q检验+ Z% s b: M& r+ z* v* k; E* Y
No statistical significance, 无统计意义
* C, U! B6 ^0 A' \Nominal variable, 名义变量" c( z' M0 }- J z. W# P
Nonconstancy of variability, 变异的非定常性
; v. K! A1 U% R, ^; f: NNonlinear regression, 非线性相关' H5 x6 U5 k; Q
Nonparametric statistics, 非参数统计
* h0 Z* k5 K& l" J& P% t3 JNonparametric test, 非参数检验0 d2 B# c6 w3 s, i( q6 E( [9 m
Nonparametric tests, 非参数检验: M( h; o1 O& g7 h
Normal deviate, 正态离差1 ~$ i& h. X6 Q
Normal distribution, 正态分布! t! O1 P* T4 y8 ?) N$ ]8 }
Normal equation, 正规方程组- d* ~0 W1 z5 G$ W! J
Normal ranges, 正常范围" c/ H3 L6 d* U4 h0 x$ j! O
Normal value, 正常值& g3 N6 h L% J
Nuisance parameter, 多余参数/讨厌参数+ U, ~& Q" ]% N$ Y4 R
Null hypothesis, 无效假设 6 L' I: w2 ]% A- A7 {- `7 G3 m
Numerical variable, 数值变量
8 N* J" B9 d+ e! o; A' K5 yObjective function, 目标函数
Y5 |5 _7 [; U" g( r2 SObservation unit, 观察单位
# e0 t2 `2 g9 I! p0 m; i5 vObserved value, 观察值
# W4 J( U8 O+ _! g3 d/ ?. U0 }One sided test, 单侧检验
* ?; l( g) D" [One-way analysis of variance, 单因素方差分析. c! \( Z# v" Y/ ]+ o% {: ]# K# a
Oneway ANOVA , 单因素方差分析
; j. v# o8 E+ K/ f& P" I) r) SOpen sequential trial, 开放型序贯设计2 `) c; g) Y u# C% E' w/ e& a: T! t7 \
Optrim, 优切尾
5 U3 c7 w e( G5 o5 y6 r( K; P8 M9 EOptrim efficiency, 优切尾效率 I @( y2 ]! j
Order statistics, 顺序统计量
' \ _- }6 S9 `5 T- X% POrdered categories, 有序分类
( J1 ?* R& {3 b4 e5 j3 d2 R+ I1 LOrdinal logistic regression , 序数逻辑斯蒂回归
! a4 ?; H+ g; @8 p) h1 F5 Y- `Ordinal variable, 有序变量1 }# i5 a# A- T$ o- }, u
Orthogonal basis, 正交基& }: ]! _' \& U/ @3 W' I: ~
Orthogonal design, 正交试验设计
$ C* A/ U4 N+ G2 V! S% Z3 e( sOrthogonality conditions, 正交条件
4 I( B& B8 k5 ]$ L. }+ I kORTHOPLAN, 正交设计 6 y6 x* B7 t. E" f
Outlier cutoffs, 离群值截断点& |* W0 B7 k5 U' G5 x! ]
Outliers, 极端值
! {8 B" Q" f' \: Z' ^# O, zOVERALS , 多组变量的非线性正规相关 4 m% a3 a" m1 E1 d1 H
Overshoot, 迭代过度
4 A- a6 f; O: m% j2 a( ePaired design, 配对设计
8 X% C7 N% E0 o! pPaired sample, 配对样本
) F' A4 Z7 q3 }, d4 Q) }. lPairwise slopes, 成对斜率1 x& ]* ^ y" Q' E! x. C
Parabola, 抛物线
8 ]/ A% [$ U" A% s; l7 K7 zParallel tests, 平行试验- {! d' P% U, x& A4 h
Parameter, 参数% {( D- p* s! y) s
Parametric statistics, 参数统计; X" V E7 k& b8 p7 o9 d5 b
Parametric test, 参数检验
x5 Q6 ~& C% @# \Partial correlation, 偏相关; Y" g& P2 C+ D% i! S
Partial regression, 偏回归9 k% C% `0 r! f9 Z+ h$ E. c: l
Partial sorting, 偏排序' J: y H1 w3 }% l4 G+ j- c- T
Partials residuals, 偏残差5 M r, c7 B% q" l9 K
Pattern, 模式
' q+ m1 O& a) ]' D4 v- @) J6 fPearson curves, 皮尔逊曲线9 O2 a) B6 ?2 k( P: B
Peeling, 退层! G6 L9 n" R5 Z2 |5 _
Percent bar graph, 百分条形图7 D! R& X$ \0 l4 j; f; M- Q x
Percentage, 百分比
. w7 F' a. ^5 r5 k/ DPercentile, 百分位数5 O( y) d# g& T
Percentile curves, 百分位曲线, h, R% N+ ^! M( E; N
Periodicity, 周期性& d2 U6 r( k# w4 g! [
Permutation, 排列
, r/ a) B: X0 e9 ? @P-estimator, P估计量
3 x# a. e+ g( |# r) yPie graph, 饼图, H, L( I, I$ B0 n4 H
Pitman estimator, 皮特曼估计量
' E) i2 ^# V9 G9 T: g1 Q3 a" a/ GPivot, 枢轴量7 L* v/ B2 i% ~" K% t7 [
Planar, 平坦3 Z: L0 A- a6 Y" v$ m# L5 Q' m8 ?
Planar assumption, 平面的假设2 F5 `* s9 f% R! s, Q. R2 p
PLANCARDS, 生成试验的计划卡
9 L/ J& w' z! CPoint estimation, 点估计
" K9 A- s1 H; {$ RPoisson distribution, 泊松分布
# A3 z. i8 @9 a' k, \' d4 `$ fPolishing, 平滑8 k$ h# }$ E U7 e) X" c( K
Polled standard deviation, 合并标准差# k$ i5 {* c6 o0 V
Polled variance, 合并方差
! J' x+ u3 f6 v* x" o Q; nPolygon, 多边图
% Y- O* F6 _0 @/ ]5 z, q- TPolynomial, 多项式
' s5 Y6 A t' n3 \) _! |Polynomial curve, 多项式曲线
$ _ Y" A- t* M' xPopulation, 总体
& w% N/ J: g7 U6 ^* w8 JPopulation attributable risk, 人群归因危险度
* h i, j8 L V* ?% ~Positive correlation, 正相关
% H; D9 H4 R: S7 }( GPositively skewed, 正偏
; P/ g4 z G8 }5 `) BPosterior distribution, 后验分布
6 e" n+ N' h6 @7 E( IPower of a test, 检验效能4 {( x( @1 J* s4 {5 R! j
Precision, 精密度
6 O4 V4 O, q* |( |Predicted value, 预测值$ l$ @8 w4 c' g. v- |
Preliminary analysis, 预备性分析# K7 Q% l8 K( y# o0 _
Principal component analysis, 主成分分析+ P" _7 a% k+ X+ m
Prior distribution, 先验分布0 \- w9 C+ ~+ O/ f% J. Q9 }4 \
Prior probability, 先验概率
5 _0 v. R2 v( L' d6 m0 vProbabilistic model, 概率模型; O* q, ?, |7 m7 a) J/ M
probability, 概率& h( x% p; ]7 F$ |; z( Y* j
Probability density, 概率密度4 y3 M. [1 w+ e* F ], C
Product moment, 乘积矩/协方差, N, L' D- {; q9 A% y9 K4 n, v7 z
Profile trace, 截面迹图
1 n* z4 y" f0 [4 r4 ?Proportion, 比/构成比% \3 t2 `4 l$ a9 s8 X, c
Proportion allocation in stratified random sampling, 按比例分层随机抽样
# o$ A- b- E# M) b" dProportionate, 成比例
3 n' u1 p7 F' R; T4 d/ gProportionate sub-class numbers, 成比例次级组含量
+ w. U( [+ O$ b' W+ ?, M" qProspective study, 前瞻性调查5 a) e2 p* a" d1 V0 _' n/ t/ D
Proximities, 亲近性
9 r# x" `9 C- Y& Q# d8 q! j9 ePseudo F test, 近似F检验1 G+ P8 g# o6 {' }% T
Pseudo model, 近似模型' S8 B# ?0 C, Q, d: s: I' R6 U% E# F
Pseudosigma, 伪标准差/ j- s' n3 m( Z& g+ a, S
Purposive sampling, 有目的抽样' o& P) x. K7 m- k
QR decomposition, QR分解
4 B1 e; w" G G1 V( c8 e$ vQuadratic approximation, 二次近似
: Q/ u8 v) k6 R& e, o( LQualitative classification, 属性分类$ x* r4 v/ Q2 W4 k0 c
Qualitative method, 定性方法5 v8 A. U0 K1 b4 e. R: g9 O$ z/ e9 y
Quantile-quantile plot, 分位数-分位数图/Q-Q图: |2 A" P* C9 L/ n( k+ l# a; e6 p
Quantitative analysis, 定量分析 }! W/ i% _9 b1 X! ^; |5 ~, |: v
Quartile, 四分位数
% m2 ?! T) U) Y4 G( EQuick Cluster, 快速聚类( a, d5 q1 [9 c8 b# V% e& o5 n
Radix sort, 基数排序
4 r; a6 g( ]. _7 t) l9 l, bRandom allocation, 随机化分组
1 w: v- [: m' v8 MRandom blocks design, 随机区组设计
6 I8 N \$ C$ K- y2 d* T% yRandom event, 随机事件
/ J( U. j+ r8 v" bRandomization, 随机化
! x) ]& X0 Q, j) z" k1 `. D# |Range, 极差/全距- C f; s/ K$ t. ?6 P8 v1 c& a, K
Rank correlation, 等级相关! u& F% W' g4 @, p8 V3 F% |$ B: |
Rank sum test, 秩和检验) ^5 m& T/ z( p" Y
Rank test, 秩检验
9 @$ B/ t( P/ mRanked data, 等级资料7 r7 N! _' U$ P2 t% S3 M
Rate, 比率
/ o9 r6 j0 M- l: D* E6 m$ u9 mRatio, 比例/ r& v% `$ D* t; v/ k. A. N
Raw data, 原始资料1 T, R* G' Z! s6 ~. h5 v: v
Raw residual, 原始残差
. x6 R9 o9 C5 L! o5 qRayleigh's test, 雷氏检验8 @/ M8 G0 G, j, c0 B
Rayleigh's Z, 雷氏Z值
$ T2 `* T: Y8 b4 X& |# a$ |; z5 LReciprocal, 倒数+ Y1 u- ^6 h9 a/ `2 j4 H1 S) N
Reciprocal transformation, 倒数变换: H$ \( S! H" A8 {
Recording, 记录
* L5 A3 c/ }2 W+ `3 F9 ^2 @Redescending estimators, 回降估计量
# g7 `5 J5 v; Y7 a9 v# v% AReducing dimensions, 降维
0 T# D' Z! O, YRe-expression, 重新表达* l) {0 i {4 ~/ O) d* w! Q
Reference set, 标准组- I" x7 ^3 L6 y
Region of acceptance, 接受域
`( |, j, ]7 E4 N. \Regression coefficient, 回归系数. u+ W- x ^+ X' \, g1 K, t0 e
Regression sum of square, 回归平方和
- d' w, X) c/ u: dRejection point, 拒绝点8 T. ]+ Q. \. h8 D/ V, i# R" u
Relative dispersion, 相对离散度
w p7 ^% y) pRelative number, 相对数& P' v+ F# x% V9 Y7 P
Reliability, 可靠性
P& Y1 n0 x4 z8 o" L4 U2 d- `) YReparametrization, 重新设置参数
# Q9 |9 \9 Y3 s! Z4 `1 [Replication, 重复
- ~8 [, |7 S2 ~7 K; _Report Summaries, 报告摘要
) G7 e- @" ^# K+ N7 OResidual sum of square, 剩余平方和6 Q& u8 S9 Q) B2 A3 s" E) ^# Q
Resistance, 耐抗性
/ U# z: P6 r$ B: I/ d: H/ [Resistant line, 耐抗线- R$ Q) z; C, C
Resistant technique, 耐抗技术
1 q0 j$ }9 Z9 |1 H q" {5 o, `5 KR-estimator of location, 位置R估计量
: W6 P' e1 R: y: mR-estimator of scale, 尺度R估计量
3 ]/ N, p4 J0 N% B* |Retrospective study, 回顾性调查 Q9 m$ l( m& ?$ s; D0 X" x# m
Ridge trace, 岭迹
' G% I8 }* m8 ^9 DRidit analysis, Ridit分析
9 y& F% X3 I" I+ e1 G. m+ DRotation, 旋转) o) h: i2 c0 b2 r" F
Rounding, 舍入
3 ?2 L3 g; x; g1 ~- f/ n4 ^ KRow, 行7 ~+ t9 n {& e" Z, j
Row effects, 行效应
6 I+ u5 B6 Q. U" \4 yRow factor, 行因素0 ]. M5 V1 j* \7 M. |% ~
RXC table, RXC表5 w4 P" o1 W! E$ A* i
Sample, 样本4 V* A u1 s* A2 Q, O6 v0 g7 h
Sample regression coefficient, 样本回归系数6 W% n1 }8 ?$ Y6 Y3 x- ?
Sample size, 样本量. z4 X! N# w4 {2 k8 m8 @
Sample standard deviation, 样本标准差
+ [6 S9 a) i) ^+ {5 q. ySampling error, 抽样误差
/ R5 q% K/ v# R2 y+ @: g, `SAS(Statistical analysis system ), SAS统计软件包9 ]6 p* G/ I% n8 }# `3 b A9 J+ ?
Scale, 尺度/量表 v9 h. U4 Q: _
Scatter diagram, 散点图
. J$ S/ ]$ Q+ k Y. U5 h: x' BSchematic plot, 示意图/简图7 y' }" \) R4 W* w2 x9 u
Score test, 计分检验# W0 ~2 \0 c" I: S: @
Screening, 筛检
9 D1 z' }: s8 G1 |SEASON, 季节分析
5 H. n& h# X, |/ KSecond derivative, 二阶导数
6 e4 q' B3 L* @ B1 NSecond principal component, 第二主成分* w2 B# E v, _ O
SEM (Structural equation modeling), 结构化方程模型 8 B8 ^& V- w- Q( }# A& H6 Q$ i6 E
Semi-logarithmic graph, 半对数图3 \! \' r; o% d" h7 p4 C+ Y
Semi-logarithmic paper, 半对数格纸
6 a, p, }7 r1 jSensitivity curve, 敏感度曲线
$ V; o, }% ?( Z' Y; bSequential analysis, 贯序分析# Y5 s1 J4 @" I- v5 c
Sequential data set, 顺序数据集
) t3 F% H' r$ a; k# uSequential design, 贯序设计0 F1 \4 U j0 ^4 a/ J' b, a
Sequential method, 贯序法7 [3 I$ e' A8 @
Sequential test, 贯序检验法3 w6 J% e, F& c" J1 s; |# U
Serial tests, 系列试验
+ X X. f: [2 Z' `* I, a% oShort-cut method, 简捷法
- J& \5 }" c: a- T' K! SSigmoid curve, S形曲线
8 ~# R7 W: p k$ c% q' j# x$ z* n, XSign function, 正负号函数
2 q) f/ ]8 d' ~; y! ]Sign test, 符号检验
( n) g, E3 t( F5 X8 b/ L, R, GSigned rank, 符号秩8 f( `, O9 r* w* @6 I" S
Significance test, 显著性检验3 P' M j4 p" V% f% P- K6 Z
Significant figure, 有效数字. F( B; S, S4 v' s$ J
Simple cluster sampling, 简单整群抽样, N4 }/ r: b! ?3 `
Simple correlation, 简单相关/ O/ }; m% m, {' V3 ?( T! K9 Z
Simple random sampling, 简单随机抽样
" T: G8 I$ z5 gSimple regression, 简单回归! n- W, }5 Z8 z8 S" _+ B8 W
simple table, 简单表. u1 o& _2 z5 F2 o& s
Sine estimator, 正弦估计量' ^- x+ f( e- X
Single-valued estimate, 单值估计' g, w. y8 ?1 g" s# ]3 _; M, e* D
Singular matrix, 奇异矩阵( [8 x+ m2 O, o a* K
Skewed distribution, 偏斜分布
4 p+ a. E' P, s) y5 D& [2 }Skewness, 偏度
9 t+ m2 B) ~4 ~Slash distribution, 斜线分布
" c4 n9 z5 \, e/ `. x) GSlope, 斜率
3 w5 w- Q8 M& s3 \Smirnov test, 斯米尔诺夫检验
& T1 j/ F x( K) Z2 e' fSource of variation, 变异来源
4 @# W B/ r" @2 zSpearman rank correlation, 斯皮尔曼等级相关5 c7 P9 a7 n; h6 p
Specific factor, 特殊因子% a9 N" K; _% v6 G% S9 o! |
Specific factor variance, 特殊因子方差 D+ f# D2 N- ^3 g3 Y
Spectra , 频谱, i* |" b0 {3 a0 C. h9 V
Spherical distribution, 球型正态分布( X2 i L9 R' a' c0 e
Spread, 展布
- Q% I% M; a0 k. f& I, OSPSS(Statistical package for the social science), SPSS统计软件包
6 [; C9 d- X% f2 GSpurious correlation, 假性相关
& u: U9 m9 o; p/ Z! m6 PSquare root transformation, 平方根变换- |1 u. K# G4 y& y" K% K A+ v
Stabilizing variance, 稳定方差: z- }6 z& I+ t. p0 d% K
Standard deviation, 标准差
; V& |* p4 M" @, \Standard error, 标准误
& k% W" D3 i* i# d; LStandard error of difference, 差别的标准误
) Q6 e* l/ w! `& HStandard error of estimate, 标准估计误差- y8 Y2 g8 a. @
Standard error of rate, 率的标准误' ~1 v) z; v `8 \3 \
Standard normal distribution, 标准正态分布5 Q s; ~- B+ o3 T' x. Q3 Q* a
Standardization, 标准化0 u* @) [; N" b3 ~+ @7 v* H
Starting value, 起始值8 F/ \1 K" F2 L8 Q7 G0 o1 x
Statistic, 统计量- q; y/ `5 M; E$ a
Statistical control, 统计控制
9 t# r/ U1 R1 n4 N+ V2 t; v; IStatistical graph, 统计图
( \7 V( l7 V4 n- A( \$ T( J6 q3 fStatistical inference, 统计推断! a6 C3 E% y) M, w! ]$ T7 p
Statistical table, 统计表
9 n; q1 |& A; T% _0 U, d2 B( H8 pSteepest descent, 最速下降法
) |& z# { W$ F" {/ ?& C- gStem and leaf display, 茎叶图1 M. E/ [( k1 G1 x( d
Step factor, 步长因子
/ ]8 Q3 L7 |. I* Y- SStepwise regression, 逐步回归
) h) W4 T9 B1 {7 rStorage, 存
6 n5 [* M0 @: J2 FStrata, 层(复数)
3 u4 ?7 z8 m0 S3 ]: h3 Y* I+ }Stratified sampling, 分层抽样
$ l5 `5 ?) @; {. @3 ?4 H) X, @Stratified sampling, 分层抽样
, v+ D. Q. {- b" KStrength, 强度* n5 o) w3 b0 S
Stringency, 严密性
, e1 G; }. ^3 x- ~' RStructural relationship, 结构关系. q. o6 u- c; ] E+ y4 Z* Y& ^+ |
Studentized residual, 学生化残差/t化残差
. B2 o& e' M% ]& U/ O# JSub-class numbers, 次级组含量1 _# w* n: G5 e% B
Subdividing, 分割
; r+ y0 T% C. A9 E" E. q2 Q: WSufficient statistic, 充分统计量
- w/ |! i, b- [2 G% ]0 n/ ], i5 ~Sum of products, 积和
0 E1 {7 t: H1 M- F3 q% u6 Z2 VSum of squares, 离差平方和
, q. }; j8 C" |Sum of squares about regression, 回归平方和8 [7 i: y8 J+ Q3 j" k8 K
Sum of squares between groups, 组间平方和# {+ N" Z1 G7 o9 \
Sum of squares of partial regression, 偏回归平方和. u8 A8 Z. p2 X7 ]& w7 V
Sure event, 必然事件4 e+ Q" N3 P7 V5 d! p' l! ]4 _+ H
Survey, 调查. p$ f) N0 i6 E
Survival, 生存分析: z4 Z/ Y1 q: W5 L' d
Survival rate, 生存率, e' r% {2 A) w- B, m- W1 O1 `
Suspended root gram, 悬吊根图, c! K/ j& d L; }3 R! e" O
Symmetry, 对称" B$ E* |6 ^, h' h4 I
Systematic error, 系统误差# `* z1 k3 q8 d
Systematic sampling, 系统抽样, ^, E9 k" y' \4 _" l+ h2 Z
Tags, 标签
; y2 J7 z0 y5 R# f5 Z9 O, g0 ZTail area, 尾部面积
( x- t# u, \+ w) O( E# c; BTail length, 尾长$ l; Q$ f- J7 y4 {5 T
Tail weight, 尾重: x& D9 \% Y4 z8 `: l
Tangent line, 切线
# N- {4 g" U8 ^ GTarget distribution, 目标分布. ?4 ]5 a @! q% [
Taylor series, 泰勒级数% j9 \& X% g2 x) o5 x- J
Tendency of dispersion, 离散趋势
2 O0 O$ p4 g2 @ }Testing of hypotheses, 假设检验
9 S% V, }; @" Z; x; iTheoretical frequency, 理论频数
& S- `) [3 j! s; t: F% p. }% \Time series, 时间序列
2 ~) j7 T# d) l3 bTolerance interval, 容忍区间% J( t D4 W! U
Tolerance lower limit, 容忍下限
7 p3 D: s t. y" ]: [8 |, W; VTolerance upper limit, 容忍上限
$ h& @! d, q4 n8 gTorsion, 扰率
* W4 U$ U7 B+ d9 Q8 [7 VTotal sum of square, 总平方和9 z/ \! I& N9 R* E
Total variation, 总变异' q$ J9 S& `+ e. _6 p U
Transformation, 转换
! f7 S1 V' u8 q7 @( ]$ [Treatment, 处理
7 ^8 P- {' B. r3 ]$ n2 RTrend, 趋势
8 D/ T2 M1 X5 D, f4 g# ?2 iTrend of percentage, 百分比趋势) R) a$ T- `9 I |9 a- f$ `
Trial, 试验
6 `/ {) _ d$ e7 ?Trial and error method, 试错法1 F& K2 q: V9 A$ Z
Tuning constant, 细调常数
" G$ m1 u# z5 u/ oTwo sided test, 双向检验- @- C1 c! R7 l
Two-stage least squares, 二阶最小平方$ O _0 y6 C/ P9 P
Two-stage sampling, 二阶段抽样
& O# X3 ~& u+ Q* H3 m/ _Two-tailed test, 双侧检验
; Q3 h7 |4 u$ J! }* RTwo-way analysis of variance, 双因素方差分析& [+ ~0 h. Z& e& w+ F+ ?& \
Two-way table, 双向表3 G5 Q3 C D; h0 |$ G6 M) L
Type I error, 一类错误/α错误
% C0 b( R y& w E0 H T I, I; |* J+ EType II error, 二类错误/β错误! l( u/ m4 ?6 A" f. L" N
UMVU, 方差一致最小无偏估计简称+ ?4 m" F0 U4 J
Unbiased estimate, 无偏估计
( G& \& I9 {( X4 w/ @( i. q$ zUnconstrained nonlinear regression , 无约束非线性回归5 |' j5 H0 b, ^9 E; s; D O
Unequal subclass number, 不等次级组含量$ j. U3 \8 t5 S& C- Q
Ungrouped data, 不分组资料+ b7 F2 [1 R( F
Uniform coordinate, 均匀坐标
! e$ [9 C1 n! G3 v1 dUniform distribution, 均匀分布
* V( e, k; P+ k" X+ ^/ IUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
" _" [6 M: \8 ]# A! T( D: JUnit, 单元7 U* l/ K* q2 P" z
Unordered categories, 无序分类
5 U2 s5 q" Q, @, q \" V6 ^2 dUpper limit, 上限
0 A! k4 ^& w& {Upward rank, 升秩
7 O; X3 U' d9 Y( Y4 D( IVague concept, 模糊概念" b& ~( F3 e' Q L" i1 j; c$ ^
Validity, 有效性
( D/ e* S% _7 s0 h5 @ Y8 zVARCOMP (Variance component estimation), 方差元素估计
: n" _8 \# }1 N/ a. uVariability, 变异性
g5 Q5 E9 A( |6 E0 p* E! `- R% iVariable, 变量
* B. ~0 N# j5 rVariance, 方差2 J: q5 s3 t( R# d7 g8 B/ o4 ?6 z
Variation, 变异
) P& M) }% p- c3 b* f& `- c% GVarimax orthogonal rotation, 方差最大正交旋转
: |1 _. X: ], oVolume of distribution, 容积
8 R' S7 F3 C) |, Q7 `1 SW test, W检验5 Q( K; g" @1 G' \" k F# K
Weibull distribution, 威布尔分布) J& _6 V2 O/ e. e4 o' A1 }7 y
Weight, 权数
6 w" U+ r$ o' u2 P% s5 aWeighted Chi-square test, 加权卡方检验/Cochran检验/ X5 C! v6 K1 L, G7 ` I; M7 l
Weighted linear regression method, 加权直线回归
' d, Y A: W/ F0 `; l7 vWeighted mean, 加权平均数6 T2 {& c- D& _; J% G; W
Weighted mean square, 加权平均方差
; X4 h$ p) O0 xWeighted sum of square, 加权平方和5 y4 X9 r9 _ z' z9 ^
Weighting coefficient, 权重系数, g: T M( J" W3 M ]0 v8 ~! U
Weighting method, 加权法
' y, B$ M7 _; N5 ^4 v& r; ]W-estimation, W估计量
3 w3 P( {& R4 F4 O% lW-estimation of location, 位置W估计量7 n! ]1 }. _' X' H3 Q
Width, 宽度9 ?0 g7 S" H' N
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
8 o0 C* l, J& E" m7 r/ uWild point, 野点/狂点9 e* A0 k. }6 M$ J9 U
Wild value, 野值/狂值
0 [' I( A7 B, F# {Winsorized mean, 缩尾均值
0 H- E4 _5 }$ o5 cWithdraw, 失访 + f9 k1 b5 N3 @* n @" z1 K8 ?+ X* b
Youden's index, 尤登指数
2 Z/ M" V( F% ]( [( |Z test, Z检验" |% O. X Y9 t, v# W
Zero correlation, 零相关
& Z! m' ?+ p, ]2 U# T- u& T9 d& |Z-transformation, Z变换 |
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